Error Analysis

library(tidyverse)
library(ggplot2)
library(plotly)
library(gridExtra)
library(boot)



# Colorblind-friendly palette, found at 
# http://www.cookbook-r.com/Graphs/Colors_(ggplot2)/#a-colorblind-friendly-palette

cbbPalette <- c("#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7")

df <- read.csv('a3 csv values.csv')

labelConversion <- setNames(c("Bar", "Pie", "L", "H", "S"),
                            c("Bar Chart", "Pie Chart", "Luminance", "Hue", "Saturation"))

summaryBarAndPiePlot <- ggplot(df, aes(x = reorder(testType,error), error, fill=testType)) +
  stat_summary(fun = mean, geom = "bar") +
  stat_summary(fun.data = mean_cl_normal, geom = "errorbar", fun.args = list(mult = 1)) +
  ggtitle("Mean Error for all Visualization Types") +
  xlab("Visualization Type") +
  theme(plot.title = element_text(hjust = 0.5),
        legend.position = "none") +
  scale_fill_manual(values=cbbPalette) +
  scale_x_discrete(breaks = c("Bar", "Pie", "L", "H", "S"),
                   labels = c("Bar Chart", "Pie Chart", "Luminance", "Hue", "Saturation"))

print(htmltools::tagList(ggplotly(summaryBarAndPiePlot, tooltip = c("y"))))

NULL

summaryBoxPlot <- ggplot(df, aes(x=reorder(testType,error), y=error, fill=testType)) +
                  geom_boxplot() +
                  ggtitle("Box Plot of Error for all Visualization Types") +
                  xlab("Visualization Type") +
                  theme(plot.title = element_text(hjust = 0.5),
                        legend.position = "none") +
                  scale_fill_manual(values=cbbPalette) +
                  scale_x_discrete(breaks = c("Bar", "Pie", "L", "H", "S"),
                                   labels = c("Bar Chart", "Pie Chart", "Luminance", "Hue",    "Saturation"))

print(htmltools::tagList(ggplotly(summaryBoxPlot)))

NULL

summaryDensityPlot <- ggplot(df, aes(x=error, color=testType)) + 
  geom_density() +
  ggtitle("Distribution of Error for all Visualization Types") +
  scale_color_manual(values= c("#E69F00", "#F0E442", "#009E73", "#0072B2", "#56B4E9"),
                     labels = c("Bar Chart", "Pie Chart", "Luminance", "Hue", "Saturation")) +
  guides(color=guide_legend(title="Visualization Type")) +
  theme(plot.title = element_text(hjust = 0.5))


summaryDensityPlot

for (uniqueID in unique(df$userID)) {

  userDF <- subset(df, subset = userID == uniqueID)
  
  if (nrow(userDF) >= 25) {
  
    userSummaryPlot <- ggplot(userDF, aes(x=reorder(testType,error), y=error, fill=testType)) +
    stat_summary(fun = mean, geom = "bar") +
    stat_summary(fun.data = mean_cl_normal, geom = "errorbar", fun.args = list(mult = 1)) +
    ggtitle(paste("Error Summary for User", uniqueID, sep = " ")) +
    xlab("Chart Type") +
    theme(plot.title = element_text(hjust = 0.5),
          legend.position = "none") +
    scale_color_manual(values=cbbPalette) +
    scale_x_discrete(breaks = c("Bar", "Pie", "L", "H", "S"),
                                   labels = c("Bar Chart", "Pie Chart", "Luminance", "Hue",    "Saturation"))
  
    print(htmltools::tagList(ggplotly(userSummaryPlot, tooltip=c("y"))))
    
  }
}

NA